collateral and secured debtrampini/papers/secured... · 2021. 6. 16. · secured debt...

Collateral and Secured Debt

Adriano A. Rampini S. ViswanathanDuke University Duke University

SFS Cavalcade North America 2021Session on Collateral and Restructuring

May 26, 2021

Adriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Theory to Distinguish between Secured Debt and CollateralSecured debt

Explicit collateralization: lien on specific assets, recovered in default

Secured lenders’ strong claim on assets enables higher leverage

Entails costs: direct or indirect (operational flexibility)

Unsecured debt

Backed by unencumbered assets, implicitly collateralized

Key insights

Collateral restricts both secured and unsecured debt

Constrained firms use more secured debt within and across firms

Consistent with stylized facts and evidence from causal forest

Bulk of debt secured for most firms

Positive relation between secured debt and financial constraints

Positive relation between leverage and tangible assets


Why Do We Care?

Collateral central to macro finance and corporate finance

Kiyotaki/Moore (1997)

Rampini/Viswanathan (2013)

Recent puzzles on secured debt

Secured debt acyclical/countercyclical – Azariadis et al. (2016)

Limited use of secured debt by large firms – Lian/Ma (2021)

Secular decline in secured debt – Benmelech et al. (2019)

No distinction between secured debt and collateral!

Punchline

Collateral is essential to understanding capital structure


Law Perspective on Secured Debt

Based on Mann (1997)

Benefits of secured debt: enforcement of payment

“increases the lender’s ability to collect the debt forcibly throughliquidation of the collateral”

“enhances the lender’s remedy (so that the lender can coercepayment more quickly than it could if its debt were not secured)”

Costs of secured debt

Direct costs, such as information and transactions costs

Indirect costs, such as operating flexibility

“you just don’t have the same flexibility of dealing with yourproperties as if you owned them unencumbered”

Very similar to basic trade-off in our model


Law Perspective on Secured Debt

Trade off depends on firms’ financial condition

“as a borrower’s financial strength increases, secured credit becomesa less attractive alternative: its benefits decrease and its costs atbest, remain constant” – Mann (1997)

“borrowers exhibit an increasing tendency toward unsecured debt astheir financial strength increases” – Mann (1997)

“unsecured creditors frequently choose to waive negative pledgecovenants in exchange for a quid pro quo, such as becoming equallyand ratably secured” – Schwarcz (1997)

Contracting in the shadow of the law

Borrowers and lenders are “reacting to the ‘shadow’ of the law – theparties’ anticipation of what would happen if formal legalproceedings were to occur” – Mann (1997)


Outline

(1) Stylized facts

(2) Model

Key distinction between secured and unsecured debt

Simple, deterministic model

Stochastic model with quantitative evaluation

(3) Secured debt and leasing (time permitting)

(4) Evidence from causal forest


Stylized Facts on Secured Debt

Data

Compustat; 1981-2018; annual; excluding SIC 6000-6999

Secured debt: Debt/Mortgages & Other Secured (DM)

Debt: Long-Term Debt (DLTT) + Debt in Current Liabilities (DLC)

Assets: Assets (AT)

Two key stylized facts

Fact 1: Secured debt increases with financial constraints

Fact 2: Leverage increases with tangible assets


Stylized Fact 1 – Secured Debt and Financial ConstraintsFinancial structure across rating deciles Model Long-term debt

Panel A: Secured debt/Assets Panel B: Secured debt/Total debt

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]

Credit rating deciles

0.0

0.1

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0.5

0.6

Secu

red

debt

leve

rage

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

0.2

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0.8

1.0

Secu

red

debt

ratio

Panel C: Unsecured debt/Assets Panel D: Debt/Assets

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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Unse

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[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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Leve

rage

Cross section: constrained firms have a lot more secured debtAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Stylized Fact 1 – Secured Debt and Financial Constraints

Assets and dividend payout across rating deciles

Panel E: Log assets Panel F: Dividends/Assets

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


19

20

21

22

23

24

25

Log

asse

ts

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.00

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Divi

dend

s-as

sets

ratio

Firms with low ratings are smaller and pay lower (or no) dividends

Low rated firms seem more constrained


Stylized Fact 1 – Secured Debt and Financial ConstraintsWithin-firm variation: heterogeneous effects of downgrades


B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]

Previous rating decile

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ange

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[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


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Chan

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B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


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[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


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Chan

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Firms that are downgraded shift to secured debt, esp. low-rated onesAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt


Shift to secured debt, esp. low-rated firms

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.04

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ange

in se

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d/un

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SecuredUnsecured



Within-firm variation: Assets & payout effect of downgrades

Panel E: Log assets Panel F: Dividends/Assets

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.3

0.2

0.1

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Chan

ge in

Log

ass

ets

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.005

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Chan

ge in

Div

iden

ds-a

sset

s rat

ioDowngraded firms downsize and reduce payout substantially



Financial structure and assets across size decilesPanel A: Secured debt/Assets Panel B: Secured debt/Total debt

1 2 3 4 5 6 7 8 9 10Assets deciles

0.00

0.05

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0.35Se

cure

d de

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1 2 3 4 5 6 7 8 9 10Assets deciles

0.0

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1.0

Secu

red

debt

ratio


1 2 3 4 5 6 7 8 9 10Assets deciles

0.0

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1 2 3 4 5 6 7 8 9 10Assets deciles

0.0

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Leve

rage

Financial constraints measure: size; small firms high fraction secured



Assets and dividend payout across size deciles

Panel E: Log Assets Panel F: Dividends/Assets

1 2 3 4 5 6 7 8 9 10Assets deciles

14

16

18

20

22

24

Log

asse

ts

1 2 3 4 5 6 7 8 9 10Assets deciles

0.00

0.01

0.02

0.03

0.04

Divi

dend

s-as

sets

ratio

Dramatic size pattern in dividends


Stylized Fact 2 – Financial Structure and Tangible AssetsFinancial structure and assets across tangibility deciles


1 2 3 4 5 6 7 8 9 10Tangible assets ratio deciles

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Secured debt and total leverage increase substantially with tangibility


Stylized Facts – Secured Long-Term Debt RatioRatio of secured debt to long-term debt

Panel A: Secured LT debt ratio by ratings Panel B: Secured LT debt ratio by assets

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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1.0Se

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tio

1 2 3 4 5 6 7 8 9 10Assets deciles

0.0

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1.0

Secu

red

debt

ratio

Panel C: ∆ Secured LT debt ratio Panel D: Secured LT debt ratio by tangibility

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.04

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Chan

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Patterns in secured LT debt still more pronouncedAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Model with Secured and Unsecured Debt

Environment

Discrete time, infinite horizon: t = 0, 1, 2, . . . .

Risk-neutral firm discounts at rate β ∈ (0, 1); limited liability

Net worth w0 at time 0

Two types of capital: tangible and intangible (fixed proportions)

Leontief aggregator k ≡ min{kp/ϕ, ki/(1− ϕ)}; ϕ ∈ (0, 1] tangible

Capital k yields cash flow A(z′)f(k) with productivity A(z′)

z′ follows Markov chain with transition function Π(z, z′) on z′ ∈ ZCapital k depreciates at rate δ ∈ (0, 1)

Production function

Decreasing returns and Inada condition

Assumption 1. Production function f strictly increasing, strictlyconcave, f(0) = 0, limk→0 f

′(k) = +∞, and limk→+∞ f′(k) = 0


Secured vs. Unsecured DebtFinancing

Intangible capital (1− ϕ)k internally financed

Tangible capital ϕk can be financed with secured and unsecured debt

Encumbered capital ks explicitly pledged to secured lenderUnencumbered capital ku = ϕk − ks backs unsecured debt

Collateralizability θs and cost κ of secured debt – Mann (1997)

Benefit: “increas[es] the lender’s ability to collect the debt forciblythrough liquidation of the collateral” and “enhanc[es] the lender’sremedy (so that the lender can coerce payment more quickly than itcould if its debt were not secured)”

Cost (direct and indirect): “[y]ou just don’t have the same flexibilityof dealing with your properties as if you owned them unencumbered”

Assumption 2. 1 > θs > θu ≥ 0 and κ > 0

Benefits and costs of secured and unsecured debt

Assumption 3. R−1(θs− θu)(1− δ) > κ > (R−1−β)(θs− θu)(1− δ)

Alternative: encumbered capital less efficient (indirect cost)

ϕk = ku + φks with φ < 1


Deterministic Model with Secured & Unsecured DebtSimplified model without uncertainty

No uncertainty (A′ constant); no intangible capital (ϕ = 1)

Firm’s problem

v(w) = max{d,ks,ku,w′,b′s,b

′u}∈R4

+×R2d+ βv(w′) (1)

subject to budget constraints for current and next period

w +∑j∈J

b′j ≥ d+∑j∈J

kj + κks (2)

A′f(∑

j∈Jkj

)+∑j∈J

kj(1− δ) ≥ w′ +∑j∈J

Rb′j (3)

collateral constraints on secured and unsecured borrowing

θjkj(1− δ) ≥ Rb′j , ∀j ∈ J , (4)

where J ≡ {s, u}.Adriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Deterministic Model – First-order ConditionsNotation

Multipliers on constraints (2) to (4): µ, βµ′, and βλ′j

Multipliers on non-negativity constraints for kj and d: νj and νd

Let k ≡∑j∈J kj

First-order conditions

µ = 1 + νd (5)

µ = βRµ′ + βRλ′j , ∀j ∈ J , (6)

µ(1 + κ) = βµ′[A′fk(k) + (1− δ)] + βλ′sθs(1− δ) + νs (7)

µ = βµ′[A′fk(k) + (1− δ)] + βλ′uθu(1− δ) + νu (8)

βµ′ = βvw(w′) (9)

Envelope condition: vw(w) = µ (marginal value of net worth)

Note: λ′u = λ′s ≡ λ′


Model with Secured and Unsecured DebtDown payments and investment Euler equation

Down pmts: ℘s = 1−R−1θs(1− δ) + κ; ℘u = 1−R−1θu(1− δ)Firm’s investment Euler equation (IEE)

1 = βµ′

µ

A′fk(k) + (1− θj)(1− δ)℘j

+νj/µ

℘j, ∀j ∈ J . (10)

Choice between secured and unsecured debt

Rewrite IEEs using Jorgenson’s (1963) frictionless user cost u ≡ r+ δ

u+Rκ+Rλ′

µ′℘s ≥ A′fk(k) (11)

u+Rλ′

µ′℘u ≥ A′fk(k), (12)

with equality if kj > 0

Trade-off between cost of encumbering assets and down payments

Assumption 3 implies ℘s < ℘u (otherwise secured debt dominated)

Secured debt enables more borrowing/higher leverage


Model with Secured and Unsecured DebtUsing IEEs we get

1 = βµ′

µ

(θs − θu)(1− δ)℘u − ℘s

+νu/µ− νs/µ℘u − ℘s

(13)

Let Rs ≡ (θs−θu)(1−δ)℘u−℘s

> R (by Assumption 2)

Secured debt is more costly

Severely constrained firms (w → 0) use secured debt only

(2) & (4) ⇒ w ≥∑j∈J ℘jkj and kj → 0, ∀j ∈ J ⇒ k → 0

IEE implies βµ′/µ→ 0; then (13) implies νu > 0

Dividend-paying firms (d > 0) use unsecured debt only

Firm pays dividends in steady state: µ = µ′ = 1, so βµ′/µ = β

By Assumption 3 Rs > β−1; then (13) implies νs > 0

IEE: 1 = β A′fk(k)+(1−θu)(1−δ)

℘uimplicitly defines k̄

Firms indifferent between secured and unsecured debt

From (13): βµ′/µ = R−1s ; IEE defines k < k̄


Model with Secured and Unsecured Debt: Characterization

Given Assumptions 1 to 3, ∃ thresholds 0 < ws < w̄s < w̄ < +∞

Financing policy

w ≤ ws: issue only secured debt

w ∈ (ws, w̄s): substitute from secured debt to unsecured debt

w ≥ w̄s: use only unsecured debt

Investment k increases in w; strictly if w ≤ ws, w ∈ [w̄s, w̄]

Payout policy: firms with w > w̄ pay dividends

Firm life cycle

Over time, firms accumulate net worth, ...

... increase investment,

... substitute from secured debt to unsecured debt,

... and eventually initiate dividends.


Model with Secured and Unsecured Debt with Uncertainty

Stochastic productivity

Assumption 4. ∀z+, z ∈ Z 3 z+ > z, (i) A(z+) > A(z),(ii) A(z) > 0

Firm’s problem

v(w, z) = max{d,ks,ku,w′,b′s,b

′u}∈R4

+×R2Sd+ βE[v(w′, z′)|z] (14)

subject to budget constraints for current and next period, ∀z′ ∈ Z,

w + E[∑j∈J

b′j

∣∣∣z] ≥ d+1

ϕ

∑j∈J

kj + κks (15)

A′f( 1

ϕ

∑j∈J

kj

)+

1

ϕ

∑j∈J

kj(1− δ) ≥ w′ +∑j∈J

Rb′j (16)

and collateral constraints (4) ∀{j, z′} ∈ J × Z


Model with Secured and Unsecured DebtInvestment Euler equation (IEE)

1 = E

[βµ′

µ

A′fk(k) + (1− ϕθj)(1− δ)℘ϕj

∣∣∣∣∣ z]

+ϕνj/µ

℘ϕj

(17)

where ℘ϕj ≡ 1− ϕ+ ϕ℘j

Severely constrained firms (w → 0) use secured debt only

(15) & (4) ⇒ w ≥ 1ϕ

∑j∈J ℘

ϕj kj ⇒ kj → 0, ∀j ∈ J ; k → 0

IEE implies βµ′/µ→ 0, ∀z′ ∈ Z since

1 ≥ E

[βµ′

µ

A′fk(k) + (1− ϕθj)(1− δ)℘ϕj

∣∣∣∣ z]≥ β

µ′

µ

A′fk(k) + (1− ϕθj)(1− δ)℘ϕj

Analogous argument implies νu > 0

Financially constrained firms borrow secured

Dividend-paying firms use unsecured debt only


Quantitative Evaluation

Baseline calibration based on Li/Whited/Wu (2016)

Structural estimate version of R/V (2013) model using SMM

Calibrated parameters:

β = 0.985 – avg. real 3m T-bill rate 1965-2012: 1.5%

R−1 = 0.988 – difference due to tax wedge with τ = 20%

Estimated parameters:

f(k) = kα and α = 0.6

A(z′) = exp(z′) with σz = 0.5 and ρz = 0.5

Not used: δ = 0.04; θ = 0.4

Our parametrization

Symmetric two-state Markov chain with Π(z, z) = 0.75 to match ρz

δ = 0.1

ϕ = 0.6: Falato/Kadyrzhanova/Sim/Steri (2018)

Calibrated: θs = 0.8; θu = 0.6; κ = 0.01


Quantitative EvaluationFinancial structure by net worth Data Causal Forest


0 2 4 6 8 10

Current net worth

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Current net worth

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Secured debt and leverage decrease with net worth


Stylized Fact 1 – Secured Debt with Leasing Skip

Financial structure and leasing across rating decilesPanel A: Secured debt/Assets (lease-adj.) Panel B: Secured debt/Total debt (lease-adj.)

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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bt le

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ease

-adj

.)

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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red

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ratio

(lea

se-a

dj.)

Panel C: Leasing debt/Assets (lease-adj.) Panel D: Debt/Assets (lease-adj.)

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

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[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.2

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Leve

rage

(lea

se-a

dj.)

Cross section: accentuated patterns and higher levelAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Stylized Fact 1 – Secured Debt and LeasingWithin-firm variation: heterogeneous effects of downgrades

Panel A: Secured debt/Assets (lease-adj.) Panel B: Secured debt/Total debt (lease-adj.)

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.01

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Chan

ge in

Sec

ured

deb

t lev

erag

e (le

ase-

adj.)

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


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ge in

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ured

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io (l

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-adj

.)


B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.000

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Chan

ge in

Lea

sing

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rage

(lea

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B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.01

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ge in

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ase-

adj.)

Firms that are downgraded shift to secured debt and leasingAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Stylized Fact 1 – Secured Debt and Leasing

Shift to secured debt (incl. leasing), esp. low-rated firms

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


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SecuredUnsecured


Stylized Fact 1 – Secured Debt and Leasing

Financial structure and leasing across size deciles


1 2 3 4 5 6 7 8 9 10Assets (lease-adj.) deciles

0.0

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Secu

red

debt

leve

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(lea

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debt

ratio

(lea

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dj.)



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rage

(lea

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0.0

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rage

(lea

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dj.)

Bulk of financing secured in all but largest firms


Stylized Fact 2 – Financial Structure and Tangible Assets

Financial structure and leasing across tangibility deciles


1 2 3 4 5 6 7 8 9 10Tangible assets ratio (lease-adj.) deciles

0.0

0.1

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Secu

red

debt

leve

rage

(lea

se-a

dj.)


0.0

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ratio

(lea

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rage

(lea

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0.0

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rage

(lea

se-a

dj.)

Secured debt, leasing, and total leverage all increase with tangibility


Stylized Facts – Secured LT Debt Ratio (Lease-Adj.)Ratio of secured debt to long-term debt (lease-adj.)

Panel A: Secured LT debt ratio by ratings Panel B: Secured LT debt ratio by assets

[D,B] B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.0

0.2

0.4

0.6

0.8

1.0Se

cure

d de

bt ra

tio (l

ease

-adj

.)


0.2

0.4

0.6

0.8

1.0

Secu

red

debt

ratio

(lea

se-a

dj.)

Panel C: ∆ Secured LT debt ratio Panel D: Secured LT debt ratio by tangibility

B+ BB- BB

[BB+,BBB-]BBB

BBB+ A-[A,A+]

[AA-,AAA]


0.06

0.04

0.02

0.00

0.02

0.04

0.06

0.08

0.10

Chan

ge in

Sec

ured

deb

t rat

io (l

ease

-adj

.)


0.0

0.2

0.4

0.6

0.8

1.0

Secu

red

debt

ratio

(lea

se-a

dj.)

Patterns in secured LT debt still more pronouncedAdriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Model with Secured and Unsecured Debt and LeasingBenefits and costs of leasing kl

Monitoring cost m > 0; leasing fee ℘l ≡ R−1u+m

Assumption 5. R−1(1− θs)(1− δ) > m− κ > 1−θsθs−θu κ

Implies ℘s > ℘l and Rl ≡ (1−θs)(1−δ)℘s−(R−1u+m)

> Rs

Repossession advantage: Eisfeldt/Rampini (2009); R/V (2013)

Firm’s problem

v(w, z) = max{d,ks,ku,kl,w′,b′s,b

′u}∈R5

+×R2Sd+ βE[v(w′, z′)|z] (18)

subject to budget constraints for current and next period, ∀z′ ∈ Z,

w + E[∑j∈J

b′j

∣∣∣z] ≥ d+1

ϕ

∑j∈J

kj + κks +1− ϕ+ ϕ(R−1u+m)

ϕkl

A′f( 1

ϕ

(∑j∈J

kj + kl))

+1

ϕ

(∑j∈J

kj + (1− ϕ)kl

)(1− δ) ≥ w′ +

∑j∈J

Rb′j

and collateral constraints (4) ∀{j, z′} ∈ J × Z

Prediction: Most constrained firms lease; then borrow secured; ...Adriano A. Rampini and S. Viswanathan Collateral and Secured Debt

Effect of Downgrades – Inference using Causal Forest Skip

Estimate heterogeneous treatment effects using causal forest

Method: Wager/Athey (2018); Athey/Wager (2019)

Application to covenant violations: Gulen/Jens/Page (2019)

Primer on causal forest

Non-parametric machine learning based estimation method

Intuitively: nearest neighbor method with adaptive neighborhood

Classification and regression trees (CARTs): tree with leavesGrow tree by recursively splitting sample by covariatesMaximize variance of treatment effects across leaves

Honest (causal) tree splits sample into training and estimation set

Causal forest aggregates causal trees to allow inferenceObtain consistent, asymptotically normal treatment effect

Our causal forest: 4000 trees using 50% of sample, 50% honesty

Outcome var: financial structure, assets, and payout policy;treatment: downgrade

Covariates: SecDebt, UnsecDebt, Debt, NetInc, MktCap, Div (all/Assets); SecDebt/Debt; Rating; MktCap; Assets; Tangibility


Causal Forest – Treatment Effect Densities

Density of conditional avg. treatment effects (CATEs)

Treatment: ratings downgrades by one notch (or more)Effect on secured debt leverage and secured debt ratioDensities for treatment effects on the treated (TT) and control (TC)

0

10

20

30

40

−0.10 −0.05 0.00 0.05 0.10Secured debt leverage

Den

sity

Treated Untreated

0

10

20

−0.10 −0.05 0.00 0.05 0.10Secured debt ratio

Den

sity

Treated Untreated

Estimates of average treatment effects ATE/ATT/ATC


Causal Forest – Heterogenous Treatment Effects Model

Treatment effect of one-notch (or more) downgrade by rating

Secured debt/Assets Secured debt/Total debt

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

Unsecured and Total Debt Assets and Dividends


Causal Forest – Treatment Effects (Lease-adj.)


Secured debt/Assets (lease-adj.) Secured debt/Total debt (lease-adj.)

0.00

0.05

D C

CC B B

B B

BB

− AA

AA

A

Rating code

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

Leasing and Unsecured Debt


Conclusion

Secured debt enables higher leverage but entails costs

Explicit collateralization gives secured lender strong claim on assets

More constrained firms use more secured debt within and across firms

Collateral restricts both secured and unsecured debt

Unsecured debt backed by unencumbered assets

Consistent with stylized facts and evidence from causal forest

Collateral is essential to understanding capital structure

Collateral constraints matter despite large firms borrowing unsecured

Firms shift to secured debt when constrained

Bulk of debt secured for small firms and lease-adj. for most firms

Unsecured debt implicitly collateralized


Average Treatment Effects from Causal ForestEffects on financial structure, investment, and payout policy

ATE/ATT/ATC: Average Treatment Effect; on Treated; on Control

Outcome variable ATE ATT ATC

Secured debt /Assets 0.021 0.016 0.022(6.973) (5.602) (6.962)

Secured debt/Total debt 0.032 0.025 0.033(5.629) (4.914) (5.563)

Unsecured debt/Assets 0.018 0.011 0.019(4.753) (3.230) (4.829)

Debt/Assets 0.040 0.027 0.042(9.740) (7.340) (9.803)

Log assets (level) -0.101 -0.110 -0.099(-8.746) (-11.220) (-8.222)

Dividends/Assets -0.004 -0.003 -0.004(-11.329) (-12.098) (-10.998)


Average Treatment Effects from Causal Forest

Treatment Effects on Financial Structure (Lease-adj.)

Outcome variable ATE ATT ATC

Secured debt /Assets 0.024 0.020 0.025(8.753) (7.415) (8.719)

Secured debt/Total debt 0.016 0.019 0.015(3.464) (4.453) (3.236)

Unsecured debt/Assets 0.012 0.005 0.013(3.956) (1.559) (4.186)

Debt/Assets 0.038 0.026 0.040(10.620) (8.059) (10.703)

Leasing debt/Assets 0.014 0.016 0.014(7.677) (9.153) (7.328)

Back


Causal Forest – Heterogenous Treatment Effects


Unsecured debt/Assets Total debt/Assets

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

Assets and Dividends Back


Causal Forest – Heterogenous Treatment Effects


Assets Dividends/Assets

−0.4

−0.2

0.0

0.2

D C

CC B B

B B

BB

− AA

AA

A

Rating code

−0.02

−0.01

0.00

0.01

D C

CC B B

B B

BB

− AA

AA

A

Rating code

Back


Causal Forest – Treatment Effects (Lease-adj.)


Leasing debt/Total debt (lease-adj.) Unsecured debt/Assets (lease-adj.)

−0.05

0.00

0.05

0.10

D C

CC B B

B B

BB

− AA

AA

A

Rating code

−0.04

0.00

0.04

0.08

D C

CC B B

B B

BB

− AA

AA

A

Rating code

Back


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